Description

Using the glmnet package implementation.

Usage

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Arguments

x

Dataset.

y

Response vector. Can be of many different types for solving
different problems, see glmnet.

family

Determines the the type of problem to solve. Auto detected if
y is numeric or survival. See family for details.

nfolds

See cv.glmnet.

foldid

See cv.glmnet.

alpha

Regularization parameter, see glmnet.

lambda

Regularization parameter, see glmnet.

...

Sent to fit_glmnet or cv.glmnet.

Details

The alpha parameter of glmnet controls the type of
penalty. Use 0 (default) for lasso only, 1 for ridge only, or
an intermediate for a combination. This is typically the parameter to tune
on. The shrinkage, controlled by the lambda parameter, can be left
unspecified for internal tuning (works the same way as
fit_glmnet).